Track: Clustering

When to use this track

Choose this path if your primary goal is partition structure (clusters / co-clustering), not just density estimation.

Path (recommended)

1. Theory: clustering extension
2. ex15 — Tail-aware clustering (weights + covariates)
3. ex16 — Bulk-only clustering (parameter links + covariates)

Outputs to understand

• Labels: representative partition (Dahl-style) plus assignment scores.
• PSM: posterior similarity matrix for diagnostics and stability.
• Plots: use S3 plot() on cluster objects rather than constructing ad-hoc visuals.

Prereqs

• Required packages and data for this page are listed in the setup chunks above.

Outputs

• This page renders model fits, diagnostics, and summary artifacts generated by package APIs.

Interpretation

• Canonical concept page: 02 Clustering Extension
• Treat this page as an application/example view and use the canonical page for core definitions.

Next

• Continue to the linked canonical concept page, then return for implementation-specific details.